CORDIS Project
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This project develops a smart tool for predicting the performance of carbon dioxide sequestration in geological formations. It aims to enhance the safety and efficiency of CO2 storage by integrating machine learning with geochemical and geomechanical data.
Geological CO2 sequestration has gotten a lot of attention as a potential technical solution for decreasing human carbon emissions to the environment.
Numerical reservoir simulation (NRS) has been conventionally used to model subsurface reservoirs and employed in uncertainty analysis, optimization, and decision-making.
One of the challenges associated with NRS is the computational efforts required to model complex reservoir systems.
Therefore, fast proxy models are suggested for quick prediction…
NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU
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